code: def from_compressor(
      cls,
      compressor: Compressor,
      new_config_list: List[Dict],
      training_steps: int,
      evaluator: Evaluator | None = None,
  ):
      return super().from_compressor(
          compressor,
          new_config_list,
          training_steps=training_steps,
          evaluator=evaluator,
      )
  
imports: from __future__ import annotations
  from collections import defaultdict
  import functools
  import logging
  from typing import Callable, Dict, List, Literal, Tuple, overload
  import torch
  from .tools import _METRICS, _MASKS, norm_metrics, generate_sparsity, is_active_target
  from ..base.compressor import Compressor, Pruner
  from ..base.target_space import TargetType
  from ..base.wrapper import ModuleWrapper
  from ..utils.docstring import _EVALUATOR_DOCSTRING
  from ..utils.evaluator import Evaluator, TensorHook
label_desc: Use image node_id 4 for calling the TaylorPruner obj's underlying member method code with example usage: obj.from_compressor(cls, compressor, new_config_list, training_steps, evaluator) and returns: super